Browsing by Author "Tijskens, L. M. M."
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- How to analyse non-destructive data for biological variationPublication . Tijskens, L. M. M.; Schouten, R.E.; Konopacki, P.; Jongbloed, G.; Kessler, M.; Nunes, CarlaBiological variance is omnipresent. In animals, in humans, in biology, in sociology, medicine, you name it. In fact, life would be utterly boring without biological variation. Also in agricultural and horticultural produce, the ubiquitous variation causes a lot of trouble in dealing with the product in the supply chain. Basically, the majority of troubles and problems in the food production and supply chain is in one way or another related to the presence of variation between entities like individuals, up to batches, pallet loads, orchards and harvests, and down to cells and organelles. Many modern measuring techniques make it possible to analyse product entities without destroying the samples. These gathered, so-called longitudinal data, offer many advantages for extracting information. By using these techniques, it becomes possible to follow individual units (batches, fruit etc.) in time, and estimate the kinetics of change in (any) properties on an individual level. Destructively obtained data (cross-sectional data) can only be analysed at the level of mean values, neglecting completely the information on variance contained in data. Explained parts of data analysis con increase from 60-70% obtained on cross-sectional data to well over 90% obtained on longitudinal data, with the quantification of the biological variance present. The analysis of longitudinal data, however, requires a special approach and the use of special analysing techniques. The benefits of longitudinal data and their analysis using mixed effect non linear regression for extracting information on maturity and biological variance within a batch, is highlighted based on a large number of examples, already published or in preparation, covering the colour and firmness of nectarines, water loss in plums, mandarins and melons, firmness in Near Isogenic Lines of melons, colour of apples in storage and during growth. More and more papers are published that prove the usefulness for both theory and practice of the applied techniques and viewpoints on biological variation.
- Variation in apple colour and maturity. causes and similarities over orchards, management, cultivars and storagePublication . Tijskens, L. M. M.; Herold, B.; Unuk, T.; Simcic, M.; Nunes, CarlaThe colour of apples (flesh colour or skin colour) was assessed using the same individual apples repeatedly in time at three different locations, in several seasons for five different cultivars. Two experiments were conducted in the orchard, one experiment during postharvest storage. The same logistic model was applied to analyse the data, separate for each location and cultivar. Non linear mixed effects regression analysis allows to extract not only information on the kinetic parameters like reaction rate constant and potential greenness, but also on the variation present in the data. The rate constant of the decolouration process was found to be largely the same for all combinations (with one exception). The variation in biological shift factor, as an expression for maturity, seems to be independent of orchard location and only slightly dependent on orchard management procedures. The main differences observed are in the potential greenness of the apples (colmin) that vary considerably between successive seasons and between cultivars. The applied technology provides the necessary tools to analyse the effects of season and orchard management, for all locations in the study. It opens wide alleys to investigate more dedicated the effects of weather, season, management and orchard location in growing apples with a constant quality (colour) over the seasons, locations and management procedures.